MiniMax

MMiniMax M2.1OPEN

MiniMax M2.1 (MiniMax): live API pricing, context window and the best open-source alternatives, tracked daily by OpenSourceAI.tech.

Context window
205K
tokens
Input price
$0.3
per M tokens
Output price
$1.2
per M tokens
Provider
MiniMax

Prices update automatically — checked hourly against provider list prices.

See model comparisons → Compare all model prices

Benchmarks & performance

Independent benchmark scores for MiniMax M2.1, measured by Artificial Analysis. Higher is better.

9.8×
More intelligence per dollar than Claude Opus 5.
For the same budget, MiniMax M2.1 delivers 9.8 times more capability. Open weights also mean you can self-host it and pay nothing per token.
Intelligence index31.4
Math index82.7
GPQA83%
MMLU-Pro87.5%
Humanity's Last Exam22.2%
Long Context Reasoning59%
LiveCodeBench81%
SciCode40.7%
AIME 202582.7%
IFBench69.9%
τ²-Bench85.4%
Terminal-Bench Hard28.8%
💰 Blended price$0.525 / 1M tokens
📈 Value59.8 intelligence points per $
Benchmark data by Artificial Analysis

About this model

MiniMax M2.1 is an open-weight AI model by MiniMax. You can download and self-host it for free; the prices below are hosted-API list prices, tracked hourly, for when you prefer convenience over self-hosting.

Frequently asked questions

What is MiniMax M2.1?

MiniMax M2.1 is an AI language model from MiniMax. It is open-weight: you can download it and run it on your own hardware, for free. It scores 31.4 on the Artificial Analysis intelligence index.

Is MiniMax M2.1 free?

The weights are free and open — you can self-host MiniMax M2.1 and pay nothing per token. If you prefer a hosted API, list prices are $0.3 per million input tokens and $1.2 per million output tokens.

What is MiniMax M2.1 good at?

Independent benchmarks from Artificial Analysis give it GPQA 83%, MMLU-Pro 87.5%, Humanity's Last Exam 22.2%, Long Context Reasoning 59%, LiveCodeBench 81%, SciCode 40.7%, AIME 2025 82.7%, IFBench 69.9%, τ²-Bench 85.4%, Terminal-Bench Hard 28.8%. It is particularly used for mathematical reasoning.

Can I self-host MiniMax M2.1?

Yes. MiniMax M2.1 has open weights, so you can download it and run it on your own GPU or server with tools like Ollama, vLLM or llama.cpp — with no per-token cost.

Open-source alternatives

Depending on your workload, an open-weight model that you can self-host may cut costs dramatically or remove per-token pricing entirely. Our comparison pages put this model side by side with the strongest open-source contenders.

MiniMax M3MiniMaxMiniMax M2.7MiniMaxMiniMax M2.5MiniMaxMiniMax M2MiniMaxMiniMax-01MiniMaxMiniMax M2-herMiniMax